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Location: New York Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. ABOUT THE ROLE: We’re looking for a Head of IT to build and own the systems that enable everyone at Modal to work effectively and securely. You’ll own our employee technology environment end-to-end, including identity and access, devices, internal systems, SaaS applications, and day-to-day IT operations. You’ll work closely with Security and Engineering to build an environment that is secure by default, easy to operate, and scales with the company. This is initially a hands-on role. You’ll build systems, automate workflows, and solve problems directly. As Modal grows, you’ll define how the IT function should scale and eventually build a team around it. WHAT YOU’LL WORK ON: Identity & Access - Own employee identity and access across internal systems and SaaS applications - Build scalable onboarding, offboarding, and access lifecycle workflows - Improve SSO, MFA, least privilege, and access management in partnership with Security Devices & Endpoints - Own the lifecycle and security of employee devices - Build and maintain device management, configuration, patching, and endpoint security - Automate provisioning and make onboarding as close to zero-touch as possible Internal Systems & Automation - Own and improve the SaaS applications and internal systems we depend on - Build integrations and automate workflows across identity, HR, finance, and other business systems - Evaluate and deploy new internal capabilities, including AI tools and integrations - Use APIs, scripting, and internal tooling to solve problems that don’t fit neatly into off-the-shelf products IT Operations - Own employee support, hardware, asset management, procurement, and relevant vendor relationships - Build reliable, maintainable processes rather than scale through manual work - Identify recurring problems and solve them at the system level Build the IT Function - Define the technical direction and operating model for IT at Modal - Establish the systems and processes we’ll need as the company grows - Determine when and where additional IT capacity is needed, and build the team over time YOU MAY BE A FIT IF: - You’ve owned IT or corporate technology in a fast-growing technology company - You have a strong understanding of identity, device management, SaaS administration, and endpoint security - You have strong technical skills and are comfortable working with APIs, scripting, automation, and system integrations - You’ve designed and automated employee lifecycle and access-management workflows - You have good security judgment and experience working closely with Security and Engineering - You can independently identify problems, make pragmatic technical decisions, and drive them through implementation - You’re comfortable being hands-on today while building the systems and team needed as the company grows

Location: New Jersey; New York; Pennsylvania; Connecticut; Massachusetts Workplace: remote About the role: At Provectus, you don’t prototype in a sandbox and hand a client a slide deck. You embed inside a bank, an insurer, or a health system, learn the work, and ship a Claude + AWS system into their real, regulated production — then you watch the business number move. We’re an Anthropic and AWS Partner with 150+ certified architects. That means the newest models, real budgets, and problems that matter — without the layers, politics, and years-to-impact of a hundred-thousand-person firm. 350+ builders, 100+ customers in production, founder-led since 2010, offices across North America, LATAM, and EMEA. Why Provectus Frontier access — Anthropic Preferred Partner: newest Claude models, real budgets, real problems. Real tasks (not scope), real deployment. You go where the operating problem is and ship production code to real users, not slide decks that sit in a drive. Embedded, not engaged. You are part of the customer’s team and inside their process — not a vendor running a project alongside it. Embedded is not staff-augmented. Autonomous. You own the work from framing through to production, visible to clients and founders.  You own the method; nobody hands you a ticket. Your experience stays portable. Every engagement is a new problem, often in a new industry, so your skills compound instead of narrowing to one product. No legacy-maintenance grind, not a single stack. Craft & growth — build beside senior FDEs on a Claude-certified team; a real platform (talks, OSS) to grow your name. We give you a stage: Claude certification, conference talks, open-source contributions, published work under your own name. Requirements: Typically 7+ years building software, a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way. Genuinely willing to spend time understanding someone else’s job before writing code; demonstrated ability to become conversant in an unfamiliar business function quickly. Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why. Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Cloud-native delivery on AWS (GCP/Azure a plus), including the operational reality of a system someone else inherits. Pre-sales experience. Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room. Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job. Hands-on experience with Claude, Claude Code, and Cowork (skills, workflows, MCP, integrations, connectors, custom harnesses). Nice to have Containers and orchestration (Kubernetes/ECS) and CI/CD in production. IaC depth: AWS CDK, CloudFormation, Terraform. Open-source contributions or public writing on applied AI. What you’ll do: Spend the first weeks of each engagement in the operator’s seat, learning the constraints from the inside, then rebuild the function from first principles alongside the client and a Forward Deployed Executive — and you are the one who builds it. Be part of the customer’s team, inside their process; work on real tasks, not scoped deliverables, and own the method autonomously. You won’t start from zero. Provectus builds industry Blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it. Deliver across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare. Help shape how leading enterprises adopt AI, from strategy through first deployment; help build the tooling and frameworks of a growing AI delivery practice. What We Offer: Full-time. On-site visits to client’s facilities and our office in NYC 1/week Unlimited Vacation policy. Generous health, vision, and dental insurance. 401(K) matching plan. Base salary $180k–$200k + bonuses; OTE up to $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, and abilities of the applicant, and alignment with market data. No Visa sponsorship We’re real: A person reads your application. We filter out AI-generated and fraudulent submissions automatically. Every application that clears that filter is read by someone on our team. We may ask for a quick ID verification. Fraudulent applications are common, and this protects real candidates. You’ll meet the people you’d work with. We host AI engineering events in New York and San Francisco. We'd be happy to talk in person. Your interviews are with Pavel Borobov, Solutions Architect, and Stepan Pushkarev, Co-Founder & CEO. How we hire: Recruitment interview. Tech interview with our FDE (30 min). A live engineering building session (1.5 hours). We hand you a business function and the constraints. You have to understand the job and rebuild it — then say what you’d build and how you’d know it worked. Use AI the way you normally would; we expect AI-generated code. What we look at is how you used AI, the judgment behind your choices, and what you researched beyond what any LLM already knows. 4. Soft skills interview. 5. Offer discussion.

Location: Bulgaria Company Background Our client is a travel technology company developing cloud-native, AI-powered software for airlines and hospitality brands. Its products help customers improve commercial performance, reduce costs, and evolve their digital commerce capabilities. The company’s technology is designed to work alongside existing airline systems, allowing customers to introduce new capabilities without replacing their current technology landscape. Project Description You will contribute to a large-scale greenfield travel-technology initiative supporting the launch of a new airline operation. The project uses a modern commercial platform to enable flexible retailing, pricing, and digital shopping experiences across travel products and ancillary services. Technologies GCP, AWS Wiz Cloudflare WAF, Bot Management, DNS, TLS, DDoS Protection and Rate Limiting Terraform SonarCloud and Dependabot Jira, PagerDuty and Slack Python and Bash What You'll Do Own and continuously improve cloud security posture across GCP organizations and AWS accounts, including connector coverage, runtime sensor deployment on production clusters, custom policy development, finding-triage baselines, and integrations with Jira, PagerDuty, and Slack; Operate and evolve the edge security layer, centralizing internet-facing protection through Cloudflare WAF, bot management, rate limiting, DNS/TLS, and origin routing for customer-facing production zones; Tune security rules using real production traffic, manage allow-list requests, and enable other teams to use edge-security tooling effectively; Support and automate vulnerability management and secure configuration, maintaining the intake of Wiz, SAST, penetration-test, and customer-reported findings, defining remediation baselines, and driving owners to closure; Participate in security incident response for cloud events, including DDoS and bot attacks, supply-chain alerts, credential exposure, and data-handling incidents, while creating and maintaining detection, triage, and mitigation runbooks; Help secure the software supply chain by owning SAST reporting in SonarCloud, dependency scanning with Dependabot, container base-image hardening, and the selection of SBOM and SCA tooling, and publish release-level security reports for engineering teams; Produce technical evidence for SOC 2, PCI DSS, ISO 27001, and NIS2, including evidence of log-sink configuration and retention, access reviews, authenticated scanning, and IAM remediation, and map Wiz controls to relevant frameworks to make evidence collection repeatable; Enable security self-service by training Platform, CloudOps, and Product Engineering teams on the tools they use, including Wiz and Cloudflare administration, mapping service catalogues to owners, and automating recurring customer-security and issue-triage reporting through scripting and AI-assisted workflows; Advise and partner with engineering teams on the security of new platform integrations and AI/RAG services, contributing to the annual cloud-security roadmap and target-state architecture; Job Requirements 5+ years of experience in cloud security or platform engineering with a security focus, including hands-on experience with GCP or AWS across IAM, audit logging, log routing, network security, and workload protection; Production experience with a CNAPP/CSPM platform, such as Wiz (preferably) / Prisma Cloud / Orca / Google Security Command Center, including policy authoring, integrations, and runtime protection; Hands-on administration of a WAF, CDN, and bot-management stack at scale; Strong Terraform experience, including building modules for security tooling and WAF configuration, reviewing changes, and managing configuration drift and legacy infrastructure; Experience with vulnerability management across cloud infrastructure, containers, and code, including SAST, SCA/dependency scanning, container image hardening, and penetration-test remediation tracking; Experience routing cloud security signals to a SIEM or security-monitoring platform, such as Wazuh, Microsoft Sentinel, Google Security Operations, or Datadog Security Monitoring, and integrating actionable alerts with PagerDuty and Slack; Scripting skills in Python or Bash for automation and security reporting; Security incident-response experience in a production environment, including developing runbooks and managing vendor escalations; Clear written and verbal communication skills, with the ability to train engineering teams and document security decisions; Nice To Have Experience automating security workflows, such as report generation and issue triage, with AI-assisted or LLM-based tooling; Experience working across both GCP and AWS, experience with Azure; Familiarity with Rego, OPA, or other policy-as-code languages; Experience with identity and access-management tooling, including Okta SSO/SCIM, PAM solutions, and least-privilege reviews for cloud IAM; Experience facilitating OWASP SAMM assessments, threat-modelling sessions, or security-champions programs; Airline or travel-industry experience, including PCI-scoped payment flows, partner integrations, and customer-facing security reporting; Experience supporting compliance with PCI DSS, SOC 2, ISO 27001, or NIS2; Certifications such as Google Professional Cloud Security Engineer, CCSP, or AWS Certified Security – Specialty; What Do We Offer The global benefits package includes: Technical and non-technical training for professional and personal growth; Internal conferences and meetups to learn from industry experts; Support and mentorship from an experienced employee to help you professional grow and development; Health insurance; Sports activities to promote a healthy lifestyle; Flexible work options, including remote and hybrid opportunities; Referral program for bringing in new talent; Work anniversary program and additional vacation days.

Задачи: — Владение полным циклом пользовательских сценариев с AI-агентом Upgrade на чат, голос и email: создание, оптимизация, обработка крайних случаев и рост показателя containment. — Создание сценариев в no-code инструменте Sierra Agent Studio, сотрудничество с продуктовыми группами для интеграции сервисных потоков. — Ответственность за разрешение проблем клиентов AI-агентом без участия человека. — Анализ и улучшение сценариев после запуска, включая чтение транскриптов и повышение качества взаимодействия. — Ведение портфеля сценариев по продуктам (Personal Loans, Card, BNPL, HELOC, Deposits) и установление стандартов разработки AI-опыта. Требования: — 3–5 лет опыта во Frontend Software Engineering или эквивалентный опыт в Solutions Engineering, Conversational AI или технических продуктовых ролях. — Знание поведения LLM-агентов: инструкции, вызовы инструментов, извлечение знаний и типичные ошибки. — Опыт построения оценок для недетерминированных систем: тестовые наборы, симуляции, LLM в роли судьи, регрессионные проверки. — Техническая грамотность для чтения API спецификаций, работы с backend-инженерами по REST и GraphQL, понимание авторизации и прав доступа. — Знание JavaScript/TypeScript для создания и поддержки кодированных сценариев и интеграции API в платформы Conversational AI. — Ориентация на продукт и клиента, умение читать транскрипты, забота о тоне общения и измерение успеха по решению проблем клиента. — Владение процессами выпуска, мониторинга, анализа логов и реагирования на инциденты. — Умение ясно писать и работать с неинженерами из операций, комплаенса и юридического отдела. Плюсы: — Опыт работы с Sierra Agent Studio или аналогичными no-code платформами (Decagon, Ada, Kore.ai, Google CCAI, Amazon Lex/Connect). — Опыт с Voice AI: распознавание речи, синтез речи, настройка задержек, обработка прерываний. — Знание систем контакт-центров, таких как Genesys, и проектирование передачи агентам. — Опыт в финтехе или регулируемых отраслях (UDAAP, FDCPA, TCPA, PCI, SOC 2). — Опыт в дизайне разговоров или UX-писательстве. Условия: — Конкурентная зарплата $140K-$180K CAD и опционный план. — Оплачиваемое медицинское, стоматологическое и офтальмологическое страхование. — Гибкий оплачиваемый отпуск. — Возможности профессионального роста и развития. — Оплачиваемый декретный отпуск. — Инициативы по здоровью и благополучию.

Самостоятельное выявление угроз, анализ рисков, расследование инцидентов и внедрение технических мер защиты. • Опыт в Cybersecurity / Information Security от 3 лет.

Location: San Francisco Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Container runtimes were designed for general-purpose software workloads. AI inference is not a general-purpose workload. Running large models at production scale exposes cracks in every layer of the container stack: runtimes unaware of GPU memory constraints, images that take minutes to pull when a model needs to scale to thousands of replicas, and isolation mechanisms that weren’t designed for the multi-tenant serving environments that production AI requires. The tools the industry has relied on for a decade weren’t built for this, and patching around those limitations at higher layers only goes so far. Baseten owns the entire pipeline, from the moment a developer pushes a model to the moment a request gets a response. That vertical ownership means we can fix these problems at the root. The Runtime Fabric team is doing exactly that: purpose-building the container runtime and storage layers for AI inference workloads, led by some of the world’s top containerd maintainers. As Engineering Manager for Storage Products on the Runtime Fabric team, you will lead the engineers who build and run the storage products behind that stack: the Baseten Delivery Network (BDN), which sits in the cold start path of every model on the platform, the snapshotters and filesystems that expose model weights and container images to a running container, and the storage that model deployment and training need next. The team is advancing the next generation of caching for inference workloads, from the origin tier to the GPU host. You will own reliability for the area as a measured outcome, report to the head of Runtime Fabric, and stay close to the code through design and code review. If you’ve managed systems engineers and have hands-on experience with caching, content-addressable storage, or distributed filesystems, we’d love to talk. EXAMPLE INITIATIVES - How the Baseten Delivery Network (BDN) makes cold starts fast https://www.baseten.co/blog/how-the-baseten-delivery-network-bdn-makes-cold-starts-fast/ - Extending BDN from model weights to container image layers, training checkpoints, and deployment artifacts - Lazy-loading snapshotters and block-level delivery (EROFS, FUSE, ublk) so a container can start before the full image or model has arrived RESPONSIBILITIES Team Leadership and Culture - Hire and grow a team of 5 to 10 systems engineers with storage, caching, and Linux expertise - Run the team’s planning and delivery: scope work against the Runtime Fabric roadmap, set priorities, and ship on a predictable cadence - Provide regular coaching, feedback, and career development support to your direct reports - Own on-call health for the team’s services, including escalation paths and follow-through on incidents Technical Direction - Guide the architecture and evolution of the Baseten Delivery Network: the tiered caching and weight delivery product that makes cold starts 2-3x faster and eliminates thundering herd failures during burst scaling events - Shape storage products tailored to Baseten’s workloads: extend BDN from model weights to container images, training checkpoints, and deployment artifacts, and define the interfaces that model deployment, training, and customers use to reach them - Oversee the on-host side of delivery: lazy-loading snapshotters, EROFS and overlayfs layouts, and block-level delivery (FUSE, ublk) for multi-gigabyte files - Own reliability of the delivery path as a measured outcome: end-to-end instrumentation from snapshotter initialization to first inference request, targets for cold start and cache behavior, tolerance for failing upstream registries and object stores, and safe rollout of changes to a path every customer depends on - Make the delivery path work across heterogeneous clusters and cloud providers, each with its own object store and network - Review designs and code across the area, and take on hands-on work where it unblocks the team - Champion the team’s contributions back to containerd and the snapshotter ecosystem alongside the maintainers on the Runtime Fabric team Cross-Functional Partnership - Act as the point of contact for storage across Baseten, ensuring model deployment, training, and platform teams have the integration support they need - Optimize requirements for the underlying storage platforms with the infrastructure team: object storage, local NVMe and block storage, and network bandwidth per cluster, so that capacity and provider decisions account for what the delivery path needs - Manage the team’s dependencies in both directions: sequence work that model deployment, training, and infrastructure teams block on, and negotiate interfaces and timelines with the teams and upstream projects the storage path depends on - Work with the head of Runtime Fabric and product stakeholders to prioritize storage investments based on customer impact and infrastructure reliability - Communicate team progress, technical trade-offs, and incidents clearly to the team and to leadership REQUIREMENTS - Experience managing a team of engineers in a systems, infrastructure, or storage context, including hiring and performance management - Hands-on background in distributed storage systems, content-addressable storage, or large-scale caching infrastructure - Strong systems programming background in Go, Rust, and/or C/C++, with the ability to engage credibly in code reviews and architectural discussions - Working knowledge of the Linux storage stack: filesystems, the page cache, block devices, and mounts - Understanding of how container images are structured, stored, and delivered at scale - Strong written and verbal communication skills, with the ability to influence without authority across teams NICE TO HAVE - Contributions to containerd/containerd, snapshotter projects (stargz, soci, nydus, overlaybd), distribution/distribution, or closely related open-source projects - Familiarity with lazy-loading snapshotters or peer-to-peer image distribution - Experience with EROFS, FUSE, ublk, or io_uring - Experience building or operating CDN, object storage, or large-scale caching infrastructure - Experience running storage services on Kubernetes BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: Stockholm ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you’ll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You’ll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You’ll own durability and cost at petabyte scale, from streaming and batch replication between origins to garbage collection over billions of objects. You’ll work across the stack, from local disk and page cache to distributed blob storage and garbage collection, and you’ll help shape what storage becomes next as we push storage closer to workloads. WHAT YOU’LL WORK ON: - Build P2P sharing of data across workers within a single datacenter to dramatically reduce ingress - Replicate data across multiple blob storage providers - Automate garbage collection across hundreds of petabytes of data - Deploy colocated storage clusters to datacenters to accelerate high-throughput customer workloads YOU MAY BE A FIT IF: - You have 5+ years of experience writing high-quality production code - You’ve built high-performance distributed storage or caching systems at a large scale (the more challenges you’ve worked through, the better) - You have strong cloud skills, including deep familiarity with object storage (S3 or similar), CDNs, and their consistency, throughput, and cost characteristics - You have strong knowledge of low-level operating system foundations (Linux kernel, file systems, page cache, containers, etc.) - You’re willing to step into the thick of it with our on-call rotation and respond to production incidents NICE-TO-HAVE: - Experience with replication, content addressing, and consistency models in multi-region or multi-cloud systems - Experience operating storage systems at scale (petabyte-scale datasets, high-throughput read/write paths, large-scale garbage collection or data migration) - Experience with data engineering at petabyte scale - Prior experience with Rust

Location: San Francisco, CA • New York, NY • United States Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma's Governance, Risk, and Compliance team is the foundation of how we build and maintain trust - with our users, regulators, business partners, and the organizations that rely on Figma every day. We work across the organization and drive programs that ensure the effectiveness of our security protections, identify and manage risk, maintain compliance, and build trust with our customers. We're looking for a Governance, Risk and Compliance Director to lead this team through its next phase of growth. You'll own Figma's security compliance, risk management, and governance strategy end to end - setting direction for our certification portfolio, building the risk and controls frameworks that scale with our growing business and product suite, and representing GRC to executives, the board, customers, and regulators. This is a hands-on leadership role where you'll manage and grow a team of GRC professionals while staying close to the programs, infrastructure, audits, and cross-functional relationships needed to both protect and enable the business. If you're a strategist and team builder who is excited to scale Figma's GRC program in a rapidly evolving environment, we'd love to hear from you! This is a full time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: Set the strategy and roadmap for Figma's GRC program, aligning compliance, risk, and governance priorities with company objectives and the Security leadership team Own Figma's certification and compliance portfolio, including SOC 2, ISO 27001, FedRAMP, SOX ITGC, and GDPR, and expand coverage as Figma enters new markets and customer segments Lead and grow a team of compliance, risk, and governance professionals, setting priorities, developing talent, and building a culture of rigor and pragmatism Build and evolve enterprise risk and controls frameworks — including AI Governance, Risk and Compliance initiatives and control effectiveness monitoring — that scale across technical and business stakeholders Manage relationships with external auditors, assessors, and regulators, and oversee audit cycles from planning through remediation Direct the selection and optimization of GRC platforms and tooling, and maintain the lifecycle of security policies, standards, and procedures Partner with Sales, Legal, and Customer Trust on security questionnaires, customer audits, contracts, and trust-related communications that support the sales lifecycle Scale enterprise risk reporting and report on program health, risk posture, and audit readiness to executive and board-level audiences We'd love to hear from you if you have: 10+ years of experience in information security, compliance, or risk management, including at least 4 years leading or managing a GRC, security, or compliance team Deep, hands-on experience with frameworks such as SOC 2 and ISO 27001, including leading programs through multiple audit cycles A track record of building GRC programs from the ground up or scaling them through high-growth stages, ideally at a SaaS or platform company, including experience operating in a public company environment with SOX ITGC requirements Executive presence and exceptional written and verbal communication skills, with demonstrated ability to build cross-functional partnerships across Security, Legal, IT, Sales, and Engineering and translate technical risk into business terms for executives, the board, and customers Experience implementing compliance programs for emerging products, including AI-enabled products, with a strong understanding of cloud-based technologies and their GRC implications, and a builder's mindset comfortable with ambiguity as the program scales While it's not required, it's an added plus if you also have: Supported FedRAMP authorization, SSP development, 3PAO coordination, or continuous monitoring activities Experience with global privacy and data protection regulations, such as GDPR or NIS2 Security or risk certifications such as CISSP, CISA, CISM, or CRISC Hands-on experience implementing or administering GRC platforms such as Vanta, Drata, or similar tools Experience presenting to boards, steering committees, and audit committees At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. Pay Transparency Disclosure Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location. Figma offers equity to employees, as well as a competitive package of additional benefits, including health, dental, and vision coverage; retirement benefits with company contributions; parental leave and reproductive or family planning support; mental health and wellness benefits; and paid time off. Figma provides paid sick leave, holidays, and other leave benefits in compliance with applicable federal, state, and local laws, including the requirements of the Washington Minimum Wage Act and related regulations. Exempt employees are eligible for employer‑provided paid flexible PTO in addition to flexible paid sick leave. PTO is subject to manager approval. Additional benefits may include company recharge days, cell phone and home internet reimbursements, and a number of lifestyle spending accounts. Figma also offers sales incentive compensation for most sales roles and an annual bonus plan for eligible non-sales roles. All compensation and benefits are subject to applicable plan terms and may be modified by Figma at any time, consistent with applicable law. Annual Base Salary Range: $235,000 — $317,000 USD At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status , or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to accommodations-ext@figma.com . These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities. Examples of accommodations include but are not limited to: Holding interviews in an accessible location Enabling closed captioning on video conferencing Ensuring all written communication be compatible with screen readers Changing the mode or format of interviews To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding. By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice . Application limits: To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles: Candidates may submit up to 5 applications during any rolling 30-day period. Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection. Once the applicable days has passed, candidates are welcome to apply again.

Location: San Francisco, CA • New York, NY • United States Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Order Management sits at the center of how Figma turns contracts into revenue — every deal our Sales team closes passes through this team before it's invoiced. As part of the Revenue Operations team within Accounting, we own order form review, invoicing, and billing support for Sales and Support for a global customer base. As Figma grows, we're building the order-to-cash process for what comes next, and this role is a builder's seat: you'll take on our most complex orders while helping shape how orders get processed, reviewed, and automated as we scale. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: Own the order process end to end — from contract review and order entry through to invoicing — processing orders accurately and within SLA, including our most complex work with validation for completeness, accuracy and policy compliance Serve as a go-to resource for Sales and Support on billing and invoicing questions, and partner with cross functional partners to investigate discrepancies and booking blockers across systems — following up to conclusion Detail-review routine orders processed by other analysts and our BPO partners, identifying error patterns and driving them to resolution Play a key role in UAT for new products, SKUs, pricing models, and billing system releases — writing and executing test scripts, running end-to-end tests from order through billing, documenting bugs clearly, and working with cross functional partners to resolve Support month-end and quarter-end close, including reconciliations, accruals, and data integrity across systems, while maintaining SOX controls, audit documentation, and the SOPs and test cases your areas run on Take ownership of ad-hoc projects related to process improvement, system upgrades, or controls enhancements across the order-to-cash lifecycle We'd love to hear from you if you have: 3+ years of experience in order management, order-to-cash, billing operations, or revenue operations at a SaaS company Hands-on experience with Salesforce (RLM or CPQ), an ERP such as NetSuite, and a payment processor such as Stripe Clear understanding of how order entry decisions flow downstream into billing and revenue Advanced Excel and Google Sheets skills — pivots, XLOOKUP, reconciling large datasets across systems — and comfort with data query tools Exceptional attention to detail and a track record of producing quality work under quarter-end pressure, with excellent written and verbal communication across finance and non-finance audiences At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. Pay Transparency Disclosure Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location. Figma offers equity to employees, as well as a competitive package of additional benefits, including health, dental, and vision coverage; retirement benefits with company contributions; parental leave and reproductive or family planning support; mental health and wellness benefits; and paid time off. Figma provides paid sick leave, holidays, and other leave benefits in compliance with applicable federal, state, and local laws, including the requirements of the Washington Minimum Wage Act and related regulations. For non-exempt employees, PTO is accrued at a rate equivalent to 15 days per year for full‑time employees. Accrued PTO may be used for vacation or personal time, subject to company policy and manager approval. In addition, the company provides 10 paid sick days annually for non-exempt full-time employees. Additional benefits may include company recharge days, cell phone and home internet reimbursements, and a number of lifestyle spending accounts. Figma also offers sales incentive compensation for most sales roles and an annual bonus plan for eligible non-sales roles. All compensation and benefits are subject to applicable plan terms and may be modified by Figma at any time, consistent with applicable law. Hourly Base Pay Range: $50.50 — $73.60 USD At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status , or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to accommodations-ext@figma.com . These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities. Examples of accommodations include but are not limited to: Holding interviews in an accessible location Enabling closed captioning on video conferencing Ensuring all written communication be compatible with screen readers Changing the mode or format of interviews To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding. By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice . Application limits: To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles: Candidates may submit up to 5 applications during any rolling 30-day period. Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection. Once the applicable days has passed, candidates are welcome to apply again.

Location: Canada; United States Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ We are hiring a Legal Operations Analyst to support the day-to-day operations of Docker's lean Legal team: contract operations, outside counsel spend, legal technology administration, and the processes that connect Legal to the rest of the business. You will report to the VP and Head of Legal with direct collaboration and oversight from the Sr. Manager of Legal Operations, and partner with Sales, Deal Desk, Finance, Product, and Engineering. You will work inside Docker's legal technology stack (Ironclad, Brightflag, Salesforce, and Zip) and the AI-assisted workflows we are actively building, with real ownership of your workstreams and direct influence on how those tools evolve. RESPONSIBILITIES - Manage contract intake, routing, approvals, and signature coordination, keeping stakeholders informed throughout the process. - Review contracts using Docker’s playbooks and AI tools, and flag nonstandard terms or questions for attorney review. - Support outside counsel billing operations, including invoice review, billing guideline compliance, and accrual tracking. - Support administration of legal technology platforms, including workflow maintenance, user support, and data quality. - Use and help improve AI-assisted workflows for contract review, drafting, and intake, including refining prompts and testing outputs against approved playbooks and attorney feedback. - Support pilots of new AI tools and use cases, gathering user feedback and tracking accuracy, adoption, and time savings. - Develop and maintain standard operating procedures, templates, and knowledge resources, and train stakeholders on legal technology and responsible AI use. - Build and maintain dashboards tracking contract volume, cycle times, and outside counsel spend, translating data into actionable insights. - Support systems integration and process improvement projects with cross-functional teams, identifying opportunities for automation and AI to streamline legal operations. QUALIFICATIONS REQUIRED - 3+ years of experience in legal operations, contract management, a paralegal role, or a related operational role, including experience at a SaaS or technology company. - Hands-on experience using a contract lifecycle management (CLM) platform, such as Ironclad, Icertis, Agiloft, or DocuSign CLM. - Experience supporting contract intake, review coordination, or signature processes. - Hands-on experience applying AI tools to legal or operational tasks, including drafting prompts, reviewing outputs for accuracy, and refining results. - Strong organizational skills, attention to detail, and the ability to manage competing requests. - Good judgment about when to follow established procedures and when to ask questions or escalate. - Clear written and verbal communication skills and the ability to collaborate and follow through on assigned work in a remote team. - Bachelor’s degree or equivalent professional experience. PREFERRED - Direct experience with Ironclad, Wordsmith, Brightflag, or similar systems. - Familiarity with invoice review, accrual tracking, or outside counsel billing. - Familiarity with Salesforce, Zip, or other systems connected to legal workflows. - Experience maintaining reports, playbooks, standard operating procedures, or training materials. - Experience supporting a small in-house legal team. - Exposure to SaaS agreements, order forms, or commercial open-source licensing. - Experience helping test or improve AI-assisted workflows. This role is a strong fit for someone who enjoys hands-on operational work, likes systems and processes, and wants to expand their use of AI in legal operations. You’ll build expertise with guidance from the Senior Legal Operations Manager, focusing on process execution, technology support, and continuous improvement. WHAT TO EXPECT FIRST 30 DAYS - Complete onboarding and become familiar with Docker’s legal tools, contract playbooks, and AI guidelines. - Shadow contract intake, invoice review, and routine Ironclad administration. - Meet key cross-functional partners and learn how Legal supports their teams. - Begin handling straightforward requests with guidance. FIRST 90 DAYS - Handle routine contract intake and initial playbook-based reviews, escalating questions to the appropriate team member. - Assist with Brightflag invoice review, accrual tracking, and spend reporting. - Support everyday Ironclad maintenance, user requests, and data cleanup. - Use existing AI-assisted workflows and help test improvements with team guidance. ONE YEAR - Reliably handle routine contract and billing workflows, recognizing when to seek guidance. - Help stakeholders navigate legal tools, processes, and contract status questions. - Maintain accurate reports, playbooks, and training resources. - Contribute to process improvements and AI tool testing that help the team reduce manual work. Docker does not offer visa sponsorship for this role.   Compensation & Equity Canada: CA$141,145– CA$201,635 + equity United States: $103,600 – $148,00 + equity ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: San Francisco, CA; Seattle, WA Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ Docker is looking for a Senior Software Engineer to build AI-powered developer tools and the platform behind them on our AI Developer Tools team. You will work at the intersection of AI, developer experience, and platform engineering, building tools that make Docker's engineers more productive and the platform that lets teams across Docker prototype, deploy, and scale their own AI developer tools. As a Senior Engineer you will design, build, and operate: AI-Powered Developer Tools. AI agents and tools that accelerate developer productivity, surface observability insights, and automate operational reviews. You will help teams adopt an AI-native way of working and speed up adoption of tools such as Claude Code and Codex. Examples include AI-powered code review and refactoring assistants, automated test generators and local environment setup tools, deployment pipeline diagnostic agents, and agents that simplify on-call work during incidents. Self-Service AI Developer Tools Platform. Platform infrastructure that lets product and platform teams across Docker unblock themselves by prototyping, building, and deploying their own AI developer tools, using the patterns and standards the team sets. You will report to the Senior Manager, AI Developer Tools, and work closely with the team's Principal and Staff engineers, product engineering teams, and platform teams across Docker. WHAT WOULD MAKE SOMEONE SUCCESSFUL IN THIS ROLE You are a strong, hands-on engineer who enjoys building at the intersection of AI, developer experience, and platform engineering. You have built software on top of LLMs and AI agents and have a good sense of what works in practice. You care about the people using your tools, and you can tell a tool developers love from one they put up with. You take a feature from a vague request to production: you ask the right questions about requirements, design it sensibly, ship it iteratively, and operate it afterward. You are comfortable in a fast-moving AI landscape and balance quality with pragmatism. You make the engineers around you better through thoughtful code review and by sharing what you learn. RESPONSIBILITIES Building and Operating AI Developer Tools - Design, build, and operate production AI agents for developer productivity, including code review assistants, test generators, deployment diagnostics, and incident response automation - Integrate LLM providers, agent orchestration frameworks, and MCP servers into reliable tools, following the team's patterns and standards - Build systems that help Docker's engineers adopt AI-native development tools - Build integrations between AI developer tools and existing developer infrastructure such as CI/CD pipelines, observability platforms, and deployment systems - Instrument your tools so the team can measure adoption, effectiveness, and developer satisfaction Self-Service Platform - Build and improve platform capabilities, including deployment pipelines (ArgoCD/GitOps), observability integration (Grafana), security controls, and cost management, that help teams ship their own AI tools faster - Help reduce time-to-production for new products from weeks to days - Contribute to reliability, security, and performance standards for AI systems, including SLOs, monitoring, and incident response Design and Delivery - Take features and services from requirements to production. Ask about scale, users, and constraints before designing, and write down your assumptions - Write clear design documents for the work you own, and participate in design reviews for the team - Review code thoroughly and share what you learn with the rest of the team - Take part in the team's on-call rotation, and help improve alerts, runbooks, and tooling so the next incident is easier - Follow the AI-assisted engineering practices the team sets: use AI tools critically, validate their output, and stay accountable for what you ship Collaboration and Growth - Work with the Senior Manager and the team's Principal and Staff engineers to understand priorities and shape your work - Partner with Infrastructure, Security, and Data teams on integrations and shared standards - Help newer engineers get up to speed on the team's tools, patterns, and practices - Keep up with emerging AI/LLM technologies and agent frameworks, and bring useful findings back to the team QUALIFICATIONS REQUIRED - 6+ years of software engineering experience building and operating production systems - Hands-on experience building LLM-powered applications, AI agents, or AI-assisted developer tools - Working knowledge of LLM APIs (OpenAI, Anthropic, and others), prompt engineering, agent orchestration frameworks, and practical uses of AI in software development workflows - Experience building and operating scalable backend services, distributed systems, or developer-facing platforms - Experience with cloud-native infrastructure, including Kubernetes, CI/CD pipelines, and observability systems - Proficiency in Go (preferred), Rust, Java, or Python, with strong software engineering fundamentals - Experience building developer tools, platform systems, or internal tools that other engineers rely on - Good product judgment: you weigh developer experience and technical trade-offs, and you ask clarifying questions before committing to a design - Clear written and spoken communication suited to a remote, async-first company - Ownership mentality with a bias for action and iterative delivery in ambiguous, fast-moving environments - Comfortable working autonomously in a distributed, remote-first team - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience PREFERRED - Experience with MCP (Model Context Protocol) or similar AI agent integration standards - Background in developer productivity, DevOps, SRE, or platform engineering - Contributions to open source AI tools, developer tooling, or platform engineering projects - Experience with GitOps deployment patterns (ArgoCD) or Grafana-based observability - Familiarity with security and operational practices for production AI systems - Experience with infrastructure-as-code (Terraform, Pulumi) and major cloud platforms (AWS, GCP, Azure) WHAT TO EXPECT FIRST 30 DAYS - Learn Docker's current AI and developer tooling landscape, the team's services, and the architecture decisions made so far - Meet your teammates, including the Principal and Staff engineers, the Senior Manager, and key stakeholders in product engineering - Ship a useful production change in your first weeks, using the team's AI-assisted engineering workflow - Review existing AI tool prototypes and internal experiments to learn what is working and what is not - Shadow on-call and learn the operational profile of the team's services FIRST 90 DAYS - Own a feature or service from design to production with measurable impact, such as part of an AI code review agent, a deployment diagnostic agent, or an on-call assistant - Write the design document for work you own and take part in team design reviews - Contribute to the self-service platform's deployment pipeline, observability integration, or security controls - Take part in the on-call rotation FIRST YEAR OUTLOOK - Be a go-to engineer for one or more of the team's AI tools or platform components - Have shipped multiple production improvements that Docker engineers use every day, with adoption and effectiveness you can point to - Have helped teams outside AI Developer Tools build and run their own tools on the platform - Have taken on larger and more ambiguous work as your scope grows, and helped newer engineers do the same Docker considers visa sponsorship on a case-by-case basis based on business needs.   Compensation & Equity United States: $160,900 – $260,700 + equity ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: San Francisco, CA; Seattle, WA Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ Docker is looking for a Staff Software Engineer to set the technical direction for key parts of our AI Developer Tools team. You will work at the intersection of AI, developer experience, and platform engineering, building the AI-powered tools and the platform that let teams across Docker prototype, deploy, and scale their own AI developer tools. As a Staff Engineer you will own the technical design and delivery for two areas: AI-Powered Developer Tools. Design and build AI agents and tools that accelerate developer productivity, surface observability insights, and automate operational reviews. You will help teams adopt an AI-native way of working and speed up adoption of tools such as Claude Code and Codex. Examples include AI-powered code review and refactoring assistants, automated test generators and local environment setup tools, deployment pipeline diagnostic agents, and agents that simplify on-call work during incidents. Self-Service AI Developer Tools Platform. Design and build the platform infrastructure that lets product and platform teams across Docker unblock themselves by prototyping, building, and deploying their own AI developer tools. You will set the patterns and standards that let teams experiment, iterate quickly, and graduate successful prototypes into production-ready services. You will report to the Senior Manager, AI Developer Tools, and work closely with the team's Principal engineers, engineering leadership, product engineering teams, and platform teams across Docker. WHAT WOULD MAKE SOMEONE SUCCESSFUL IN THIS ROLE You are a hands-on technical leader who works well at the intersection of AI, developer experience, and platform engineering. You have shipped production systems built on LLMs and AI agents, and you can explain what worked and what did not. You think in platforms: you design something once so that several teams can move faster. You have clear opinions about what makes a developer tool good, and sound judgment about when to build, when to integrate, and when not to do either. You are comfortable in a fast-moving AI landscape and balance technical quality with shipping iteratively. Before you design, you ask about scale, users, and constraints rather than assuming them. You lead through influence and mentorship, and the engineers around you get better because you are on the team. RESPONSIBILITIES Technical Leadership and Architecture - Set technical direction and own the architecture for AI-powered developer tools and the self-service platform within the team's roadmap - Turn ambiguous problems into clear requirements, plans, and staged decisions. Ask about scale, users, and constraints before designing, and write down your assumptions - Establish patterns, standards, and best practices for LLM integration, agent development, and production AI systems that the team and partner teams adopt - Shape platform capabilities including deployment frameworks (ArgoCD/GitOps), observability integration (Grafana), security controls, and operational tooling for AI developer tools - Design reliable, scalable infrastructure for hosting AI agents and developer tools - Recommend AI technology choices, LLM provider strategies, and agent orchestration approaches, and make the trade-offs explicit - Work with the Senior Manager and the team's Principal engineers to align technical decisions with business goals Systems Design and Implementation - Design, build, and operate production AI agents for developer productivity, including code review assistants, test generators, deployment diagnostics, and incident response automation - Build self-service platform capabilities that reduce time-to-production for new AI tools from weeks to days - Build systems that speed up adoption of AI-native development tools (Claude Code, Codex) across Docker's engineering organization - Set and meet reliability, security, and performance standards for AI systems, including SLOs, monitoring, incident response, and cost management - Design integrations between AI developer tools and existing developer infrastructure such as CI/CD pipelines, observability platforms, and deployment systems - Take part in the team's on-call rotation and use what you learn to improve alerts, runbooks, and tooling Strategic Impact and Innovation - Evaluate emerging AI/LLM technologies, developer tooling trends, and agent frameworks, and recommend what Docker should adopt and what it should not build - Define how we measure AI tool effectiveness, including adoption, productivity gains, and developer satisfaction - Improve AI tool performance, cost efficiency, and developer experience through architectural improvements - Contribute to the technical approach for hardening proven internal tools so other teams across Docker can adopt them - Lead cross-team technical delivery, surface risks early, and work with Infrastructure, Security, and Data on shared standards Leadership and Mentorship - Mentor senior engineers on AI/LLM integration patterns, agent development, and platform engineering practices - Lead design reviews and raise the quality of design and code reviews across the team - Create reusable patterns, documentation, and architectural decision records (ADRs) that other engineers build on - Help the team turn good individual AI-assisted engineering practice into shared workflows and controls - This role may require participation in an on-call rotation to provide support outside of standard business hours, including evenings, weekends, and holidays, as needed. QUALIFICATIONS REQUIRED - 8+ years of software engineering experience, with demonstrated technical leadership on production systems at scale - Hands-on production experience building LLM-powered applications, AI agents, or AI-assisted developer tools - Strong understanding of LLM APIs (OpenAI, Anthropic, and others), prompt engineering, agent orchestration frameworks, and practical uses of AI in software development workflows - Track record of designing and building scalable distributed systems and developer-facing platforms - Production experience with cloud-native infrastructure, including Kubernetes, GitOps deployment patterns, observability systems, and CI/CD pipelines - Proficiency in Go (preferred), Rust, Java, or Python, with strong software engineering fundamentals - Experience designing developer tools, platform systems, or internal tools that other teams rely on - Track record of clarifying requirements and constraints with stakeholders before committing to a design - Track record of leading complex initiatives that crossed team boundaries, and of influencing without direct authority - Strong product and platform judgment: you weigh business outcomes, developer experience, and technical trade-offs - Clear written and spoken communication suited to a remote, async-first company - Track record of mentoring other experienced engineers - Ownership mentality with a bias for action and iterative delivery in ambiguous, fast-moving environments - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience PREFERRED - Experience with MCP (Model Context Protocol) or similar AI agent integration standards - Background in developer productivity, DevOps, SRE, or platform engineering - Contributions to open source AI tools, developer tooling, or platform engineering projects - Experience evolving an internal platform or tool into a widely adopted, production-grade service - Knowledge of security, compliance, and operational practices for production AI systems - Experience with infrastructure-as-code (Terraform, Pulumi) and major cloud platforms (AWS, GCP, Azure) WHAT TO EXPECT FIRST 30 DAYS - Build context on Docker's current AI and developer tooling landscape, including existing AI experiments, LLM provider relationships, and architecture decisions to date - Meet the Senior Manager, the team's Principal engineers, engineering leadership, and key stakeholders in product engineering to understand needs, pain points, and constraints - Review existing AI tool prototypes and internal experiments to learn what is working and what is not - Get hands-on with the team's services and ship a useful production change - Shadow on-call and learn the operational profile of the team's services - Work with the Senior Manager to agree on initial technical priorities FIRST 90 DAYS - Lead the technical framing and delivery plan for one significant problem, from requirements through to production - Document the architecture, technology choices, and integration patterns for that work, including ADRs - Ship a production AI developer tool that sets patterns the team can reuse (for example an AI-powered code review agent, a deployment diagnostic agent, or an on-call assistant) - Contribute to the technical foundations of the self-service platform: deployment pipeline, observability integration, security controls, and cost management - Lead design reviews for your area of the roadmap and begin mentoring other engineers - Take part in the on-call rotation FIRST YEAR OUTLOOK - Be the trusted technical lead for your area of AI Developer Tools, and a sought-after partner for teams across Docker - Deliver at least one material outcome that spans multiple teams or systems - Have multiple production AI tools demonstrating value across Docker's engineering organization - Help build a self-service platform that lets multiple teams build, deploy, and operate their own AI tools with little friction - Define and instrument how the team measures AI tool adoption, effectiveness, and developer productivity impact - Grow other senior engineers into broader ownership, and reduce the number of decisions that depend on a small set of people Docker considers sponsorship on a case-by-case basis based on business needs.   Compensation & Equity United States: $170,350 – $275,550 + equity ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: United Kingdom; Brazil; Ireland; Peru; Costa Rica; Latvia; Argentina; Romania; Cyprus; Portugal; Slovenia; South Africa; Czech Republic; Panama; Estonia; Canada; Hungary; Mexico; Poland; Spain; Bulgaria Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. The AI Infrastructure team builds and operates the production systems that power intelligent agents at scale. This team sits at the foundation of the agent platform, ensuring that model inference, orchestration, and execution layers are reliable, observable, and performant under real-world load. Working closely with the Agent Systems team and broader infrastructure partners, this group owns the core primitives that enable agents to safely operate across internal systems. The environment is high-scale and high-stakes — systems serve millions of users and must meet strict reliability, latency, and correctness standards. This is a deeply production-oriented team. Engineers here combine strong systems thinking with applied ML infrastructure experience, building in Rust and operating services where performance and failure modes matter.   THE OPPORTUNITY - Design and build the infrastructure layer powering AI agent systems in production - Develop high-performance Rust services that handle model inference, orchestration, and execution - Architect scalable systems capable of supporting millions of users and high request throughput - Build reliable ML infrastructure and MLOps patterns for model deployment, evaluation, and monitoring - Define guardrails, observability, and failure handling for agent-driven workflows - Optimize latency, throughput, and cost across inference and orchestration layers - Partner closely with the Agent Systems team to translate experimental prototypes into hardened production systems - Contribute to foundational infrastructure decisions in a high-scale, high-impact environment   WHAT YOU BRING - 5+ years of experience building and operating high-scale production systems - Strong proficiency in Rust and systems-level programming - Deep understanding of distributed systems, reliability engineering, and performance optimization - Experience operating services serving millions of users or high-throughput workloads - Familiarity with ML infrastructure, model serving, or MLOps in production environments - Experience designing observability, monitoring, and failure recovery systems - Strong collaboration skills working across infrastructure and applied engineering teams - High ownership mindset in high-stakes production environment   NICE TO HAVES - Experience building infrastructure for agent-based or LLM-powered systems - Background in high-performance networking, async systems, or low-latency architectures - Experience with container orchestration and cloud-native infrastructure - Familiarity with evaluation frameworks and model performance monitoring at scale - Experience working in fast-moving 0→1 or platform-building teams Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Ищем сильного Security Engineer с практическим опытом защиты инфраструктуры, расследования инцидентов и проектирования архитектуры безопасности. • Опыт в Cybersecurity / Information Security от 3 лет.

The System & Infrastructure Administrator is responsible for the day-to-day administration, support, security, and reliable operation of the company’s corporate IT environment.

Поддержка и развитие инфраструктуры на Ubuntu 22.04/24.04; Настройка и сопровождение CI/CD в GitLab;

Развёртывать и администрировать Kubernetes-кластеры (DropApp/OpenShift): настройка ресурсов, квот. Строить и поддерживать CI/CD-конвейеры (Jenkins + Bitbucket): от сборки Docker-образов до деплоя в prod.

Location: New York; San Francisco Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. ABOUT GTM ENGINEERING: GTM Engineering is responsible for the data, business logic, workflows, and agents that enable our Marketing and Sales teams to help customers get the most out of Modal. Like the infrastructure beneath the Magic Kingdom https://en.wikipedia.org/wiki/Disney_utilidor_system, much of our work happens behind the scenes. We build systems that anticipate and deliver what customers need to grow on Modal. We bring a product management, growth engineering, and data science approach to GTM, from centralizing our data platform https://deepline.com/blog/gtm-ai-nyc-chris-modal to building agents for account research https://parallel.ai/blog/case-study-modal. THE ROLE: We’re looking for a GTM Engineer to own our GTM data platform. This role combines analytics engineering with revenue operations: you’ll build the org map, people graph, and data systems that help us discover future customers and support our GTM workflows, partnering closely with our Data team on the shared foundation. WHAT YOU’LL WORK ON: - Build and maintain an org map and people graph connecting companies, labs, teams, and individuals to identify researchers, engineers, and early-stage startups, including people beyond our existing users and CRM - Own identity resolution, enrichment, and CRM schemas so affiliations, roles, and relationships stay accurate, current, and traceable to their sources - Build GTM data models in Snowflake and dbt connecting people, companies, workspaces, workloads, usage, and revenue, giving reps and agents a shared foundation for customer context - Partner with RevOps and Marketing to define and implement metrics, data models, and business rules for routing, territory assignments, compensation, pipeline reporting, and attribution - Partner with Data on usage forecasts and account signals; build reproducible reporting that reconciles actuals, forecasts, human adjustments, and credited attainment - Build reverse ETL pipelines for ad audiences, lifecycle campaigns, CRM enrichment, outbound, and event outreach, preserving engagement history and campaign eligibility - Own data quality and system health, from graph coverage and stale enrichment to failed syncs and historical reporting accuracy - Build the tooling that helps GTM Engineering ship reliably, from development environments, automated tests, and deployments to backups and shared AI agents and skills YOU MAY BE A FIT IF: - You’re fluent in SQL and proficient in Python - You already use AI coding tools and agents to build, debug, and automate your work, and help teammates do the same - You’ve built data models and production pipelines with tools like Snowflake, dbt, Modal, or Hex - You have hands-on experience with CRM architecture, integrations, and revenue or marketing operations - You understand how leads, accounts, opportunities, and revenue move through a business - You have high attention to detail and a habit of testing, documenting, and monitoring the systems you build NICE-TO-HAVE: - Experience with usage-based businesses